A quantitative enhanced assessment for ancient landslide reactivation risk considering cross-time scale joint response mechanism

Ancient landslide has strong concealment and disturbance sensitivity due to its special geotechnical mechanical characteristics, and it is the potential hazard that cannot be ignored in human activities and major engineering planning. The quantitative assessment of ancient landslide reactivation risk has become more necessary for pre-disaster scientific warning. However, because the mechanisms of deformation and damage during the evolution of ancient landslides are quite complex, traditional landslide risk assessment methods only select the single-time scale and relatively stable environmental factors for analysis, lacking consideration of dynamic triggering factors such as rainfall. Focusing on the complexity, a quantitative enhanced assessment for ancient landslide reactivation risk considering cross-time scale joint response mechanism is proposed. First, on the basis of systematic analysis of the implicit genesis mechanism and explicit characterization, an evaluation system of the cross-time scale joint characteristics of ancient landslide reactivation is constructed. Then, XGBoost algorithm and SBAS-InSAR are used to establish the long-time scale developmental evolution mechanism model and the short-time scale dynamical trigger model, respectively. Subsequently, we propose a cross-time scale joint response mechanism. The information entropy weight method is applied to calculate the contribution degree of long-short time scale assessment models for ancient landslide reactivation based on the constraints of quantitative interval thresholds, and the assessment processes of different time scales are dynamically and quantitatively correlated. Finally, the updated optimization of the assessment of ancient landslide reactivation risk is achieved. In this research, experimental analysis was carried out for ancient landslide groups in a geological hazard-prone area in Fengjie County, Chongqing, a typical mountainous region of China. The results of the comparative analysis validate the superiority of the method in this paper. It helps to accurately assess the ancient landslide potential hazard in advance, providing scientific basis and technical support for the risk assessment of mountainous watershed geological hazards and major engineering projects

A Quantitative Modeling and Prediction Method for Sustained Rainfall-PM2.5 Removal Modes on a Micro-Temporal Scale

PM2.5 is unanimously considered to be an important indicator of air quality. Sustained rainfall is a kind of typical but complex rainfall process in southern China with an uncertain duration and intervals. During sustained rainfall, the variation of PM2.5 concentrations in hour-level time series is diverse and complex. However, existing analytical methods mainly examine overall removals at the annual/monthly time scale, missing a quantitative analysis mode that applies micro-scale time data to describe the removal phenomenon. In order to further achieve air quality prediction and prevention in the short term, it is necessary to analyze its micro-temporal removal effect for atmospheric environment quality forecasting. This paper proposed a quantitative modeling and prediction method for sustained rainfall-PM2.5 removal modes on a micro-temporal scale. Firstly, a set of quantitative modes for sustained rainfall-PM2.5 removal mode in a micro-temporal scale were constructed. Then, a mode-constrained prediction of the sustained rainfall-PM2.5 removal effect using the factorization machines (FM) was proposed to predict the future sustained rainfall removal effect. Moreover, the historical observation data of Nanjing city at an hourly scale from 2016 to January 2020 were used for mode modeling. Meanwhile, the whole 2020 year observation data were used for the sustained rainfall-PM2.5 removal phenomenon prediction. The experiment shows the reasonableness and effectiveness of the proposed method

An adaptive LIC based geographic flow field visualization method by means of rotation distance

Geographic visualization is essential for explaining and describing spatiotemporal geographical processes in flow fields. However, due to multi-scale structures and irregular spatial distribution of vortices in complex geographic flow fields, existing two-dimensional visualization methods are susceptible to the effects of data accuracy and sampling resolution, resulting in incomplete and inaccurate vortex information. To address this, we propose an adaptive Line Integral Convolution (LIC) based geographic flow field visualization method by means of rotation distance. Our novel framework of rotation distance and its quantification allows for the effective identification and extraction of vortex features in flow fields effectively. We then improve the LIC algorithm using rotation distance by constructing high-frequency noise from it as input to the convolution, with the integration step size adjusted. This approach allows us to effectively distinguish between vortex and non-vortex fields and adaptively represent the details of vortex features in complex geographic flow fields. Our experimental results show that the proposed method leads to more accurate and effective visualization of the geographic flow fields

以無人載具航拍進行河道穩定性監測之可行性研究

為瞭解拔仔溪土石流潛勢溪流經歷整治後，集水區內河道穩定趨勢，利用無人載具空拍影像產製高解析鑲嵌影像及數值地表模型，可清楚辨視河道內植生變化情形。以97年整治前航照繪製堤防線，利用自101年至103年間三期無人載具航拍影像，將各期河道內植生覆蓋範圍圈繪比對，以量化方式呈現河道穩定情形，結果顯示河道植生面積於102年增加36%，雖103年減少至27%，以長期趨勢而言河道植生覆蓋呈現成長顯見其穩定性佳。因此以傳統地形測量監測外，使用無人載具亦不失為快速便捷的方式。In order to understand the relationship between vegetation variation and the trend of river stability in Ba-tz creek after river regulation, this study proposes the use of UAV(Unmanned Aerial Vehicle) to generate high quality orthomosaic images and DSM(Digital Surface Model). To quantify the river stability, we apply UAV photograph in 2008 as basic, and analysis the area of vegetation variation in different years. Results shows that the vegetation coverage to increase 36% in 2013, to decrease 9% in 2014. Overall, the purpose of this study is to discuss the feasibility of UAV to monitor the river is a quick method besides the traditional topography surveying

Phylogenetic and Temporal Dynamics of Human Immunodeficiency Virus Type 1 CRF01_AE in China

<div><p>To explore the epidemic history of HIV-1 CRF01_AE in China, 408 fragments of gag gene sequences of CRF01_AE sampled in 2002–2010 were determined from different geographical regions and risk populations in China. Phylogenetic analysis indicates that the CRF01_AE sequences can be grouped into four clusters, suggesting that at least four genetically independent CRF01_AE descendants are circulating in China, of which two were closely related to the isolates from Thailand and Vietnam. Cluster 1 has the most extensive distribution in China. In North China, cluster 1 and cluster 4 were mainly transmitted through homosexuality.The real substance of the recent HIV-1 epidemic in men who have sex with men(MSM) of North China is a rapid spread of CRF01_AE, or rather two distinctive natives CRF01_AE.The time of the most recent common ancestor (tMRCA) of four CRF01_AE clusters ranged from the years 1990.9 to 2003.8 in different regions of China. This is the first phylogenetic and temporal dynamics study of HIV-1 CRF01_AE in China.</p> </div

Sampling information for the 222 HIV-1 CRF01_AE sequences obtained from the Los Alamos HIV sequence database.

<p>Sampling information for the 222 HIV-1 CRF01_AE sequences obtained from the Los Alamos HIV sequence database.</p

Estimated Substitution Rates and Dates for Transmission Clusters.

*<p>Estimates of the mean evolutionary rate (μ, substitutions.site⁻¹.year⁻¹) and the median time of the most recent common ancestor (tMRCA) for the different clusters (95% high posterior density in parentheses).</p

Demographic and clinical information for patients infected with CRF01_AE virus in North China.

<p>Demographic and clinical information for patients infected with CRF01_AE virus in North China.</p

Demographic and clinical information for the 186 HIV-1 CRF01_AE Infectors reported by our laboratory.

<p>Demographic and clinical information for the 186 HIV-1 CRF01_AE Infectors reported by our laboratory.</p